Effects of interaction of multiple large-scale atmospheric circulations on precipitation dynamics in China.

Different scenarios of precipitation, that lead to such phenomena as droughts and floods are influenced by concurrent multiple teleconnection factors. However, the multivariate relationship between precipitation indices and teleconnection factors, including large-scale atmospheric circulations and sea surface temperature signals in China, is rarely explored. Understanding this relationship is crucial for drought early warning systems and effective response strategies. In this study, we comprehensively investigated the combined effects of multiple large-scale atmospheric circulation patterns on precipitation changes in China. Specifically, Pearson correlation analysis and Partial Wavelet Coherence (PWC) were used to identify the primary teleconnection factors influencing precipitation dynamics. Furthermore, we used the cross-wavelet method to elucidate the temporal lag and periodic relationships between multiple teleconnection factors and their interactions. Finally, the multiple wavelet coherence analysis method was used to identify the dominant two-factor and three-factor combinations shaping precipitation dynamics. This analysis facilitated the quantification and determination of interaction types and influencing pathways of teleconnection factors on precipitation dynamics, respectively. The results showed that: (1) the Atlantic Multidecadal Oscillation (AMO), EI Niño-Southern Oscillation (ENSO), East Asia Summer Monsoon (EASM), and Indian Ocean Dipole (IOD) were dominant teleconnection factors influencing Standardized Precipitation Index (SPI) dynamics; (2) significant correlation and leading or lagging relationships at different timescales generally existed for various teleconnection factors, where AMO was mainly leading the other factors with positive correlation, while ENSO and Southern Oscillation (SO) were mainly lagging behind other factors with prolonged correlations; and (3) the interactions between teleconnection factors were quantified into three types: enhancing, independent and offsetting effects. Specifically, the enhancing effect of two-factor combinations was stronger than the offsetting effect, where AMO + NAO (North Atlantic Oscillation) and AMO + AO (Atlantic Oscillation) had a larger distribution area in southern China. Conversely, the offsetting effect of three-factor combinations was more significant than that of the two-factor combinations, which was mainly distributed in northeast and northwest regions of China. This study sheds new light on the mechanisms of modulation and pathways of influencing various large-scale factors on seasonal precipitation dynamics.

Precipitation and vegetation transpiration variations dominate the dynamics of agricultural drought characteristics in China.

Agricultural drought posing a significant threat to agricultural production is subject to the complex influence of ocean, terrestrial and meteorological multi-factors. Nevertheless, which factor dominating the dynamics of agricultural drought characteristics and their dynamic impact remain equivocal. To address this knowledge gap, we used ERA5 soil moisture to calculate the standardized soil moisture index (SSI) to characterize agricultural drought. The extreme gradient boosting model was then adopted to fully examine the influence of ocean, terrestrial and meteorological multi-factors on agricultural drought characteristics and their dynamics in China. Meanwhile, the Shapley additive explanation values were introduced to quantify the contribution of multiple drivers to drought characteristics. Our analysis reveals that the drought frequency, severity and duration in China ranged from 5-70, 2.15-35.02 and 1.76-31.20, respectively. Drought duration is increasing and drought intensity is intensifying in southeast, north and northwest China. In addition, potential evapotranspiration is the most significant driver of drought characteristics at the basin scale. Regarding the dynamic evolution of drought characteristics, the percentages of raster points for drought duration and severity with evapotranspiration as the dominant factor are 30.7 % and 32.7 %, and the percentages with precipitation are 35.3 % and 35.0 %, respectively. Precipitation in northern regions has a positive effect on decreasing drought characteristics, while in southern regions, evapotranspiration dominates the dynamics in drought characteristics due to increasing vegetation transpiration. Moreover, the drought severity is exacerbated by the Atlantic Multidecadal Oscillation in the Yangtze and Pearl River basins, while the contribution of the North Atlantic Oscillation to the drought duration evolution is increasing in the Yangtze River basin. Generally, this study sheds new insights into agricultural drought evolution and driving mechanism, which are beneficial for agricultural drought early warning and mitigation.

Revegetation affects the response of land surface phenology to climate in Loess Plateau, China.

Land surface phenology (LSP), defined as the plant's growth rhythm retrieved from satellite sensing products, is proven to shift with climate change and affect the carbon cycles of terrestrial ecosystems. Global afforested area is largely increasing and consequently affecting local and global climate. However, how and to what extent revegetation affects LSP remains relatively unexplored. Here we investigated the difference in four LSPs (i.e., greenup, maturity, senescence, and dormancy) and the response of LSP to climate between restored and native vegetation on Loess Plateau, China, where a remarkable process of vegetation restoration happened during 1982-2015. Most study regions showed a longer growing season (LOS) over time, specifically, with a slight delay in greenup but a relatively large delay in senescence. We found that air temperature was the dominant factor affecting greenup and maturity, while precipitation mostly controlled the senescence and dormancy in the study area. Under similar climate conditions, the LSP of restored vegetation (i.e., restored forest and grassland) showed a significant difference (p < 0.05) from native ones during 1999-2015. Compared to the native forest, restored forest from cropland and grassland showed a delayed greenup date by 0.3 and 3.6 days (p < 0.05) and an advanced dormancy date of 6.6 and 9.0 days (p < 0.05), respectively. Furthermore, the restored vegetation became less sensitive to air temperature than native vegetation, while the restored forest was more sensitive to precipitation, and its growth was affected by the water limitation to a larger extent in the study area. Our study highlights the necessity of considering land use management and its effect on the LSP change to better understand the effect of afforestation on global climate and carbon cycles.

Groundwater as a limited carbon dioxide source in a large river (the Yangtze River).

Groundwater discharge to river networks makes up a major source of riverine CO2 emission, available evidence however comes mainly from headwater streams which are directly connected to terrestrial ecosystems and spatially limited in terms of system size. Here relying on coupled water and CO2 mass balances, we quantified the groundwater-mediated CO2 input to the Yangtze River mainstem on an annual basis, where the mass balance of water provided physical constraints on CO2 exchange between the river and groundwater. A landscape topographic control of the groundwater-river interaction was proposed where mountain reaches preferentially receive water and CO2 discharge from the groundwater while plain alluvial reaches predominantly lose water to the aquifers. Groundwater CO2 inputs were however small in magnitude on all reaches (0.3-14% of the total CO2 emission and transport by the river) and unable to account for the discrepancy between surface evasion and internal metabolism in the river. Minor direct groundwater discharge to the reaches in comparison to smaller streams (negative to < 3.5% of the surface water flows) was concluded to be the main reason for low groundwater-sourced CO2 in the large river reaches.

Impacts of preseason drought on vegetation spring phenology across the Northeast China Transect.

Vegetation phenology is undergoing profound changes in response to the recent increases in the intensity and frequency of drought events. However, the mechanisms by which drought affects the start of the growing season (SGS) are poorly understood particularly in arid and semi-arid regions. Here, we identified varying degrees of preseason drought events and analyzed the sensitivity of the SGS to preseason drought across the Northeast China Transect (NECT). Our results showed that drought caused a delayed SGS in grassland ecosystems, but an advanced SGS within forest ecosystems. These contrasting responses to preseason drought reflected different adaptive strategies between vegetation types. The SGS was shown to be highly sensitive to short timescales drought (1-3 months) in semi-arid grasslands where annual precipitation is 200-300 mm (i.e. SAGE200-300). Biomes within this region were found to be most vulnerable out of all the ecosystems to drought. Given the frequent nature of droughts in the mid-latitudes, a drought early warning system was recommended accompanied by improved modeling of how the SGS will be affected by intensified drought under future climate change.

Changes in reference evapotranspiration and its driving factors in the middle reaches of Yellow River Basin, China.

Reference evapotranspiration (ET0) is important for agricultural, environmental and other studies, and understanding the attribution of its change is helpful to provide information for irrigation scheduling and water resources management. The present study investigates the attribution of the change of ET0 at 49 meteorological stations in the middle reaches of Yellow River basin (MRYRB) of China from 1960 to 2012. Results show that annual ET0 increases from the northwest to the southeast of MRYRB in space. We find that annual ET0 clearly presents a zigzag change pattern rather than a monotonically change during the whole period. The detected three breakpoints at 1972, 1988 and 1997 divide the whole period into four subperiods. The sensitivity analysis indicates that the ET0 is the most sensitive to surface solar radiation (Rs), followed by relative humidity (RH) and mean air temperature (T), and the least sensitive to wind speed (u) in our study area. Furthermore, we find that ET0 is becoming less sensitive to RH and more sensitive to T during 1960-2012. The attributions of the change in ET0 vary largely at different regions and subperiods. The declined wind speed is the dominant factor, followed by Rs to the ET0 reduction during 1960-2012. Further analysis shows that Rs and u are the two major contributing factors that control the change of ET0 at most stations and during most subperiods. Our study confirms that the change of ET0 is influenced by the complex interactions of climatic factors, and the dominant factor to the change of ET0 is different in various regions and time periods. The results presented here can provide a reference for agricultural production and water resources management in MRYRB as well as other semi-arid and semi-humid regions.

Characterizing and explaining spatio-temporal variation of water quality in a highly disturbed river by multi-statistical techniques.

Assessing the spatio-temporal variations of surface water quality is important for water environment management. In this study, surface water samples are collected from 2008 to 2015 at 17 stations in the Ying River basin in China. The two pollutants i.e. chemical oxygen demand (COD) and ammonia nitrogen (NH3-N) are analyzed to characterize the river water quality. Cluster analysis and the seasonal Kendall test are used to detect the seasonal and inter-annual variations in the dataset, while the Moran's index is utilized to understand the spatial autocorrelation of the variables. The influence of natural factors such as hydrological regime, water temperature and etc., and anthropogenic activities with respect to land use and pollutant load are considered as driving factors to understand the water quality evolution. The results of cluster analysis present three groups according to the similarity in seasonal pattern of water quality. The trend analysis indicates an improvement in water quality during the dry seasons at most of the stations. Further, the spatial autocorrelation of water quality shows great difference between the dry and wet seasons due to sluices and dams regulation and local nonpoint source pollution. The seasonal variation in water quality is found associated with the climatic factors (hydrological and biochemical processes) and flow regulation. The analysis of land use indicates a good explanation for spatial distribution and seasonality of COD at the sub-catchment scale. Our results suggest that an integrated water quality measures including city sewage treatment, agricultural diffuse pollution control as well as joint scientific operations of river projects is needed for an effective water quality management in the Ying River basin.